Postoperative drug-resistant bacteria infection in patients with acute Stanford type A aortic dissection under two-fluid numerical simulation model

Objective: This study was to investigate the characteristics and related factors of postoperative drug-resistant bacteria infection (DRBI) in patients with acute Stanford A aortic dissection (AD) (AAAD) based on a two-fluid numerical simulation model (TFNS model). Methods: 50 patients with AAAD admi...

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Main Authors: Sheng Zang, Yu Zhang, Jiarui Xu, Yaming Du, Sahar Issa, Saeed Hameed Kurdi Al Dulaimi
Format: Article
Language:English
Published: Elsevier 2021-07-01
Series:Results in Physics
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2211379721005167
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language English
format Article
sources DOAJ
author Sheng Zang
Yu Zhang
Jiarui Xu
Yaming Du
Sahar Issa
Saeed Hameed Kurdi Al Dulaimi
spellingShingle Sheng Zang
Yu Zhang
Jiarui Xu
Yaming Du
Sahar Issa
Saeed Hameed Kurdi Al Dulaimi
Postoperative drug-resistant bacteria infection in patients with acute Stanford type A aortic dissection under two-fluid numerical simulation model
Results in Physics
Two-fluid numerical simulation model
Type A aortic dissection
Stanford A
Drug-resistance bacteria
Infection
author_facet Sheng Zang
Yu Zhang
Jiarui Xu
Yaming Du
Sahar Issa
Saeed Hameed Kurdi Al Dulaimi
author_sort Sheng Zang
title Postoperative drug-resistant bacteria infection in patients with acute Stanford type A aortic dissection under two-fluid numerical simulation model
title_short Postoperative drug-resistant bacteria infection in patients with acute Stanford type A aortic dissection under two-fluid numerical simulation model
title_full Postoperative drug-resistant bacteria infection in patients with acute Stanford type A aortic dissection under two-fluid numerical simulation model
title_fullStr Postoperative drug-resistant bacteria infection in patients with acute Stanford type A aortic dissection under two-fluid numerical simulation model
title_full_unstemmed Postoperative drug-resistant bacteria infection in patients with acute Stanford type A aortic dissection under two-fluid numerical simulation model
title_sort postoperative drug-resistant bacteria infection in patients with acute stanford type a aortic dissection under two-fluid numerical simulation model
publisher Elsevier
series Results in Physics
issn 2211-3797
publishDate 2021-07-01
description Objective: This study was to investigate the characteristics and related factors of postoperative drug-resistant bacteria infection (DRBI) in patients with acute Stanford A aortic dissection (AD) (AAAD) based on a two-fluid numerical simulation model (TFNS model). Methods: 50 patients with AAAD admitted to our hospital from July 2018 to October 2020 were selected as the research objects. The patients were rolled into an infection group and a non-infection group according to whether DRBI occurred after surgery. There were 21 patients in the infected group and 29 patients in the non-infected group. The clinical data of the patients were collected, including preoperative, intraoperative, and postoperative conditions. A TFNS model was constructed. The construction of vascular physical model could be completed by the construction of fluid area and solid area. The blood flows through the fluid area and the blood vessel wall was located in the solid area. The model was adopted to study the characteristics of DRBI. The data of the patients were analyzed to explore the relationship of the multi-DRBI to intraoperative blood loss, postoperative complications, intensive care unit (ICU) stay time, invasive procedures, and use of antibiotics. In addition, the multi-factor postoperative multi-DRBI was performed with the regression analysis. Results: There was no significant difference between the infected group and the non-infected group in antibiotics used such as cephalosporin, penicillin, glycopeptide, and quinolones (P > 0.05). The time spent on antibiotics was greatly lower in the infected group than in the non-infected group (P < 0.05). The ICU stay time in the infected group was 17.78 ± 11.55, and that in the non-infected group was 6.67 ± 4.36, without notable difference between the two groups (P < 0.05). In addition, there was no significant difference between the two groups in the time to transfer to the ICU, while there was one case infected with Staphylococcus aureus, Pseudomonas aeruginosa, and Enterobacter cloacae. The excessive plasma loss (odds ratio (OR) = 3.823, 95% confidential interval (CI) = 1.643–8.897), renal insufficiency (OR = 1.855, 95% CI = 1.076–3.199), ICU stay time (OR = 5.089, 95% CI = 1.507–17.187), indwelling time of nasal feeding tube (NFT) (OR = 3.225, 95% CI = 1.332–7.807), assisted ventilation (OR = 3.077, 95% CI = 1.640–5.773), tracheal intubation (OR = 5.078, 95% CI = 1.415–18.227), tracheotomy (OR = 0.073, 95% CI = 0.013–0.382), continuous renal replacement (CRR) therapy (OR = 0.111, 95% CI = 0.023–0.476), use time of antibiotics (OR = 1.089, 95% CI = 1.038–1.143) were independent risk factors for postoperative multi-DRBI. Conclusion: postoperative multi-DRBI was characterized by Acinetobacter baumannii infection with the largest proportion, followed by Klebsiella pneumoniae; excessive plasma loss, renal insufficiency, ICU stay time, indwelling time of NFT, assisted ventilation, tracheal intubation, tracheotomy, CRR therapy, and use time of antibiotics were all independent risk factors of postoperative multi-DRBI. In the postoperative care of AAAD patients, the inducing factors had to be informed to the patient, and relative measures should be taken to prevention and treatment, which was conductive to reducing the incidence of infection and promote the recovery of AAAD.
topic Two-fluid numerical simulation model
Type A aortic dissection
Stanford A
Drug-resistance bacteria
Infection
url http://www.sciencedirect.com/science/article/pii/S2211379721005167
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spelling doaj-b561a849f80b4d52a4923df4f782850a2021-06-27T04:37:12ZengElsevierResults in Physics2211-37972021-07-0126104394Postoperative drug-resistant bacteria infection in patients with acute Stanford type A aortic dissection under two-fluid numerical simulation modelSheng Zang0Yu Zhang1Jiarui Xu2Yaming Du3Sahar Issa4Saeed Hameed Kurdi Al Dulaimi5Vascular Surgery, First Affiliated Hospital of Jinzhou Medical University, Jinzhou City 121000, Liaoning Province, ChinaVascular Surgery, First Affiliated Hospital of Jinzhou Medical University, Jinzhou City 121000, Liaoning Province, ChinaBreast Surgery, First Affiliated Hospital of Jinzhou Medical University, Jinzhou City 121000, Liaoning Province, ChinaVascular Surgery, First Affiliated Hospital of Jinzhou Medical University, Jinzhou City 121000, Liaoning Province, China; Corresponding author.Department of Environmental Health Sciences, Faculty of Communication, Arts and Sciences, Canadian University Dubai, Dubai, United Arab EmiratesApplied Science University, Al Eker, BahrainObjective: This study was to investigate the characteristics and related factors of postoperative drug-resistant bacteria infection (DRBI) in patients with acute Stanford A aortic dissection (AD) (AAAD) based on a two-fluid numerical simulation model (TFNS model). Methods: 50 patients with AAAD admitted to our hospital from July 2018 to October 2020 were selected as the research objects. The patients were rolled into an infection group and a non-infection group according to whether DRBI occurred after surgery. There were 21 patients in the infected group and 29 patients in the non-infected group. The clinical data of the patients were collected, including preoperative, intraoperative, and postoperative conditions. A TFNS model was constructed. The construction of vascular physical model could be completed by the construction of fluid area and solid area. The blood flows through the fluid area and the blood vessel wall was located in the solid area. The model was adopted to study the characteristics of DRBI. The data of the patients were analyzed to explore the relationship of the multi-DRBI to intraoperative blood loss, postoperative complications, intensive care unit (ICU) stay time, invasive procedures, and use of antibiotics. In addition, the multi-factor postoperative multi-DRBI was performed with the regression analysis. Results: There was no significant difference between the infected group and the non-infected group in antibiotics used such as cephalosporin, penicillin, glycopeptide, and quinolones (P > 0.05). The time spent on antibiotics was greatly lower in the infected group than in the non-infected group (P < 0.05). The ICU stay time in the infected group was 17.78 ± 11.55, and that in the non-infected group was 6.67 ± 4.36, without notable difference between the two groups (P < 0.05). In addition, there was no significant difference between the two groups in the time to transfer to the ICU, while there was one case infected with Staphylococcus aureus, Pseudomonas aeruginosa, and Enterobacter cloacae. The excessive plasma loss (odds ratio (OR) = 3.823, 95% confidential interval (CI) = 1.643–8.897), renal insufficiency (OR = 1.855, 95% CI = 1.076–3.199), ICU stay time (OR = 5.089, 95% CI = 1.507–17.187), indwelling time of nasal feeding tube (NFT) (OR = 3.225, 95% CI = 1.332–7.807), assisted ventilation (OR = 3.077, 95% CI = 1.640–5.773), tracheal intubation (OR = 5.078, 95% CI = 1.415–18.227), tracheotomy (OR = 0.073, 95% CI = 0.013–0.382), continuous renal replacement (CRR) therapy (OR = 0.111, 95% CI = 0.023–0.476), use time of antibiotics (OR = 1.089, 95% CI = 1.038–1.143) were independent risk factors for postoperative multi-DRBI. Conclusion: postoperative multi-DRBI was characterized by Acinetobacter baumannii infection with the largest proportion, followed by Klebsiella pneumoniae; excessive plasma loss, renal insufficiency, ICU stay time, indwelling time of NFT, assisted ventilation, tracheal intubation, tracheotomy, CRR therapy, and use time of antibiotics were all independent risk factors of postoperative multi-DRBI. In the postoperative care of AAAD patients, the inducing factors had to be informed to the patient, and relative measures should be taken to prevention and treatment, which was conductive to reducing the incidence of infection and promote the recovery of AAAD.http://www.sciencedirect.com/science/article/pii/S2211379721005167Two-fluid numerical simulation modelType A aortic dissectionStanford ADrug-resistance bacteriaInfection